ImageNet.
We perform experiments on ImageNet to validate the existence and effectiveness of feature transformation on large scale classification dataset.
Furthermore, we also adopt different architectures of teacher and student to validate them.
A ResNet50 is chosen to be the teacher while a ResNet18 and a MobileNetV2-0.5\(\times \)  are used to be students separately.
We compare the top-1 accuracy with other distillation method and show the results in Table REF .
The results show that knowledge discrepancy also exists in large scale classification, and equipped with our method can also further improve the performances of state-of-the-art methods [1]}[2]}[3]}.
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